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Dominate your competitors by using their keywords

The Recommended Topics feature is a special text analysis technique that provides an extraction algorithm (also known as keyword recognition or keyword analysis) that automatically extracts the most important and frequently used words and phrases from a text. It helps summarize the content of texts and identify the most important topics covered.

Blogely systematically crawls the entire data set of your top 10 competitors on a given topic and generates recommended topics (keywords) in less than a minute. This way, you can easily identify what your competitors mention most often. This saves hours of manual processing.

In other words: we identify what related terms Google expects to see on a page that can help your content rank better.

The Blogely algorithm analyzes the top Google results for your search term (the topic of the article) and performs natural language processing over them.

Two-step approach in SEO optimization

The new SEO tab in the Outline view is represented by two tabs, Focused keywords, and Recommended topics.

This is a two-step approach to content optimization:

1. Full article optimization for focus keywords – a handful (at most 1 to 3) thoroughly selected keywords.
2. Optimization of the content based on the presence of the selected topics according to the recommended (suggested) frequency.


The “Focus keywords” tab is an existing feature – primary focused keywords for SEO optimization described earlier in this video.


The newly introduced feature can be seen on the second tab “Recommended topics”. 

Note: After clicking on this tab, the red “Optimize” button will change to “Manage”.

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The user must click on the “Manage” button and go to the keyword analysis page.

Based on Natural Language Processing and our proprietary algorithm, we recommend topics and provide a suggested count.  

Users have the option of getting recommended keywords through Blogely or importing them from other platforms – such as MarketMuse, Frase, or any other system that provides it.

Relevance – is how relevant the keyword is to the search topic. It is expressed in percentage and sorted in descending order. The higher percentage – the more relevant the keyword is to the topic. 
Distributed – the actual number of the given keyword in the content. Each time the user accesses this page, it is automatically recalculated.
Suggested – is the number of times this keyword should appear in the content. It is based on the top 10 competitors analyzed for the given keyword (topic or title of the article).



Now, let’s get recommended keywords using Blogely. ​​

Get recommendations from Blogely

By default, we use the article name as the search term. It is displayed in the popup window that opens after clicking the “Get” button.

However, you can make corrections before you select OK. 

Note: The number of recommendations available per month is equal to the monthly limit for publishing articles. When the user reaches his monthly limit, the system uses credits: 1 credit = 1 search request.

Select a country out of 193 countries available. Here is the list: 

Blogely-research-countries.xlsx

Select language out of 34 languages. 

Languages we support for Recommended keywords:

#
Code
Language
1
ar
Arabic
2
bg
Bulgarian
3
br
Breton
4
cz
Czech
5
da
Danish
6
de
German
7
el
Greek
8
en
English
9
es
Spanish
10
et
Estonian
11
fa
Persian
12
fi
Finnish
13
fr
French
14
hi
Hindi
15
hr
Croatian
16
hu
Hungarian
17
hy
Armenian
18
id
Indonesian
19
it
Italian
20
ja
Japanese
21
lt
Lithuanian
22
lv
Latvian, Lettish
23
nl
Dutch
24
no
Norwegian
25
pl
Polish
26
pt
Portuguese
27
ro
Romanian
28
ru
Russian
29
sk
Slovak
30
sl
Slovenian
31
sv
Swedish
32
tr
Turkish
33
uk
Ukrainian
34
zh
Chinese

Make sure your target search query closely matches the topic you write about in your blog. 

After that select OK and wait for the results to be generated.  This process will take up to a minute. 

Voila!  The system generates up to 50 recommended topics:  

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Importing from MarketMuse or Frase

Therefore, if anyone wants to use their output for recommended topics, it isn’t a problem. By clicking the “Import” link, you can import the file in CSV format.

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CSV file has two columns.  List of keywords with a suggested count.  Topic exports from MarketMuse or Frase can be used to populate both columns. 

You can download a sample of this file here.

Format data file export from Frase:  


Format data file export from MarketMuse:  

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After the user has created or imported the recommended keyword list, it is now time to optimize the article.

  • Go to the article’s outline view.
  • While previewing the content on the right (if the Article tab is active), select the SEO tab on the left.
  • Select the “Recommended” sub-tab.
  • View all the recommended keywords on the left side.
  • You can copy any keyword and use it in their content.

Now, by clicking on the button “Scan” the user can review the optimization status.  

Column “Distr” (Distribution) – indicates the number of times this keyword (or keyword phrase) appears in the content of the article. 

Distribution color schema:

The distribution is measured by the number of suggested counts.

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Video overview

Conclusion

Search engine marketing optimization starts with identifying related keywords. The more related keywords you find, the more valuable your content can be, and you can write more SEO-friendly blog posts.

In order for your blog articles to rank well, they should be SEO-friendly and appealing to your readers. Using keywords in your blog posts can help get your website pages indexed so that your target audience can find your website pages.

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